دانلود کتاب یادگیری ماشین برای دانشمندان کامپیوتر و تحلیلگران داده از دیدگاه کاربردی

The recent popularity gained by the field of machine learning (ML) has led to its adaptation into almost all the known applications. The applications range from smart homes, smart grids, and forex markets to military applications and autonomous drones. There exists a plethora of machine learning techniques that were introduced in the past few years, and each of these techniques fits greatly for a specific set of applications rather than a one-size-fits-all approach. In order to better determine the application of ML for a given problem, it is nontrivial to understand the current state of the art of the existing ML techniques, pros and cons, their behavior, and existing applications that have already adopted them. This book thus aims at researchers and practitioners who are familiar with their application requirements, and are interested in the application of ML techniques in their applications not only for better performance but also for ensuring that the adopted ML technique is not an overkill to the considered application.We hope that this book will provide a structured introduction and relevant background to aspiring engineers who are new to the field, while also helping to revise the background for the researchers familiar with this field. This introduction will be further used to build and introduce current and emerging ML paradigms and their applications in multiple case studies.